Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19.

BACKGROUND: The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE: To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN: Retrospective cohort. SETTING: Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION: Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS: We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS: Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS: Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION: Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

Capturing what matters: A retrospective observational study of advance care planning documentation at an academic medical center during the COVID-19 pandemic.

BACKGROUND: Advance care planning allows patients to share their preferences for medical care with the aim of ensuring goal-concordant care in times of serious illness. The morbidity and mortality of the COVID-19 pandemic has increased the importance and public visibility of advance care planning. However, little is known about the frequency and quality of advance care planning documentation during the pandemic. AIM: This study examined the frequency, quality, and predictors of advance care planning documentation among hospitalized medical patients with and without COVID-19. DESIGN: This retrospective cohort analysis used multivariate logistic regression to identify factors associated with advance care planning documentation. SETTING/PARTICIPANTS: This study included all adult patients tested for COVID-19 and admitted to a tertiary medical center in San Francisco, CA during March 2020. RESULTS: Among 262 patients, 31 (11.8%) tested positive and 231 (88.2%) tested negative for SARS-CoV-2. The rate of advance care planning documentation was 38.7% in patients with COVID-19 and 46.8% in patients without COVID-19 (p = 0.45). Documentation consistently addressed code status (100% and 94.4% for COVID-positive and COVID-negative, respectively), but less often named a surrogate decision maker, discussed prognosis, or elaborated on other wishes for care. Palliative care consultation was associated with increased advance care planning documentation (OR: 6.93, p = 0.004). CONCLUSION: This study found low rates of advance care planning documentation for patients both with and without COVID-19 during an evolving global pandemic. Advance care planning documentation was associated with palliative care consultation, highlighting the importance of such consultation to ensure timely, patient-centered advance care planning.

The Impact of Hospital Capacity Strain: a Qualitative Analysis of Experience and Solutions at 13 Academic Medical Centers.

BACKGROUND: Hospital capacity strain impacts quality of care and hospital throughput and may also impact the well being of clinical staff and teams as well as their ability to do their job. Institutions have implemented a wide array of tactics to help manage hospital capacity strain with variable success. OBJECTIVE: Through qualitative interviews, our study explored interventions used to address hospital capacity strain and the perceived impact of these interventions, as well as how hospital capacity strain impacts patients, the workforce, and other institutional priorities. DESIGN, SETTING, AND PARTICIPANTS: Qualitative study utilizing semi-structured interviews at 13 large urban academic medical centers across the USA from June 21, 2019, to August 22, 2019 (pre-COVID-19). Interviews were recorded, professionally transcribed verbatim, coded, and then analyzed using a mixed inductive and deductive method at the semantic level. MAIN OUTCOME MEASURES: Themes and subthemes of semi-structured interviews were identified. RESULTS: Twenty-nine hospitalist leaders and hospital leaders were interviewed. Across the 13 sites, a multitude of provider, care team, and institutional tactics were implemented with perceived variable success. While there was some agreement between hospitalist leaders and hospital leaders, there was also some disagreement about the perceived successes of the various tactics deployed. We found three main themes: (1) hospital capacity strain is complex and difficult to predict, (2) the interventions that were perceived to have worked the best when facing strain were to ensure appropriate resources; however, less costly solutions were often deployed and this may lead to unanticipated negative consequences, and (3) hospital capacity strain and the tactics deployed may negatively impact the workforce and can lead to conflict. CONCLUSIONS: While institutions have employed many different tactics to manage hospital capacity strain and see this as a priority, tactics seen as having the highest yield are often not the first employed.